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model_zoo/index.html

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 <h2 id="2">2. 剪枝<a class="headerlink" href="#2" title="Permanent link">#</a></h2>
 <h3 id="21">2.1 图像分类<a class="headerlink" href="#21" title="Permanent link">#</a></h3>
-<p>数据：ImageNet1000类</p>
+<p>数据集：ImageNet1000类</p>
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 <h3 id="22">2.2 目标检测<a class="headerlink" href="#22" title="Permanent link">#</a></h3>
-<p>数据：Pasacl VOC &amp; COCO 2017</p>
+<p>数据集：Pasacl VOC &amp; COCO 2017</p>
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 <h3 id="23">2.3 图像分割<a class="headerlink" href="#23" title="Permanent link">#</a></h3>
-<p>数据：Cityscapes</p>
+<p>数据集：Cityscapes</p>
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 <h2 id="3">3. 蒸馏<a class="headerlink" href="#3" title="Permanent link">#</a></h2>
 <h3 id="31">3.1 图象分类<a class="headerlink" href="#31" title="Permanent link">#</a></h3>
-<p>数据：ImageNet1000类</p>
+<p>数据集：ImageNet1000类</p>
 <p>评价指标：Top-1/Top-5准确率</p>
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 <p><a name="trans1">[2]</a>：<a href="https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.tar">ResNet101</a>预训练模型Top-1/Top-5准确率分别为77.56%/93.64%</p>
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 <h3 id="32">3.2 目标检测<a class="headerlink" href="#32" title="Permanent link">#</a></h3>
-<p>数据：Pasacl VOC &amp; COCO 2017</p>
+<p>数据集：Pasacl VOC &amp; COCO 2017</p>
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